"The Singularity Is Nearer featuring Ray Kurzweil | SXSW 2024" - Transcript | YTScribe

all right I'm so excited to be here with you Ray it's great to be here great to see everybody together yeah beautiful audience so my favorite thing in that introduction of you is that you have been working in AI longer than any other human alive which means if you live forever and we'll get to that you will always have that distinction I think I think that's right uh Marvin Minsky was actually my mentor uh if he were live today he would actually be more than 61 years so and we're going to bring him back also

so maybe not sure how we'll count the distinction then all right so we're going to fix the audio but this is what we're going to do with this conversation I'm going to start out asking Ray some questions about where we are today we'll do that for a few minutes then we'll get into what has to happen to reach the singularity so the next 20 years then we'll get into a discussion about what the singularity is what it means how it change our lives and then at the end we'll talk a little bit about how if

we believe this vision of the future what it means for us today ask your questions they'll come in I'll ask them as they go in the different sections of the conversation but let's get Kraken can you hear me you can't hear Ray well this will be recorded you guys are going to all live forever there'll be plenty of time it will be fine I'm just going to get started I assume the audio will get worked out they do fabulous job here at South by I think they should be able to hear me and J all

right we got this over on the right audio Engineers are we uh are we good to go we're good to go all right all right first question Ray so you've been working in AI for 61 years oh wait can can you hear me that's not so everybody in the front can hear you but nobody in the back in hear can you hear me now okay all right I'll speak louder first question so you've been living in the a revolution for a long time you've made lots of predictions many of which have been remarkably accurate we've

all been living in a remarkable two-year transformation with large language models a year and a half what has surprised you about the Innovations in large language models and what has happened recently well I I I did finish this book a year ago and didn't really cover a large language model so I delayed the book to to cover that um but um I was expecting this that to happen like a couple of years later I mean I made a prediction in in 1999 that would happen by 2029 uh and and we're not quite there yet uh

but we will but it looks like it's maybe a year or two ahead of schedule um so that there was maybe a bit of surprise are you you you predicted back in 1999 that a computer would passed the Turing test in 2029 are you revising that to something more closer to today no I'm still saying 2029 uh the uh definition of the Turning test is not precise we're going to have people claiming that TR test has been solved and people are saying that gp4 actually passes it uh some people so it's going to be like

maybe two or three years where people start claiming and then they continue to claim and finally everybody will accept it so it's not like it happens in one day but you have a very specific definition of the Turing test when do you think we'll pass that definition well the tur test is actually not that significant because that means that that you can uh a computer will pass for a human being and what's much more important is Agi automatic general intelligence which means that it can emulate any human being so you have one computer and it

can do everything that any human being can do and that's also 2029 it all it all happens at the same time but nobody can do that I mean just take an average the large language model today you can ask it anything uh and it will answer you pretty convincingly no human being can do all of that and it does it very quickly it'll write a very nice essay in 15 seconds uh and then you can ask it again it'll write another essay and no human being can actually perform at that level right so you have

to dumb it down to actually have a have a convincing turning test to have a turning test you have to dumb it down yeah let me ask the first question from the audience since I think it's quite relevant to where we are which is Brian Daniel is the curtz curve still accurate say again is the Curts curve still accurate yes in fact it's can they see that let's pull the slides up first slide so this is an 80-year uh track record this is an exponential growth a straight line on this curve means exponential uh curvature

uh if it was sort of exponential but not quite it would curve this actually a straight line uh it started out with a computer that did [Music] 0.007 calculations per second per constant dollar that's the lower left hand corner at the upper right hand corner it's 65 billion calculations per second for the same amount of money uh so that's why large language models have only been feasible for two years PRI we actually had large language models before that but it didn't work very well um and this is an exponential curve technology moves in an exponential

uh curve we we see that for example uh having renewable energy come from the Sun and uh and wind that's actually an exponential curve uh it's in it's increased it's gone uh We've decreased the price by 99.7% um we've multiplied the amount of energy coming from solar energy a million fold so this kind of curve uh really directs all kinds of Technology um and this is the reason that we're making uh progress I mean we we knew how to do large language models years ago but we're dependent on this curve um and it's pretty amazing

and it started out increasing relay speeds then vacuum tubes then integrated circuits and each year it makes the same amount of progress approximately uh regardless of where you are on this curve we just added the last Point uh and it's again uh we basically multiply this by two every 1.4 years um and and this this is the reason that computers are exciting uh but it actually affects every type of technology and we just added the last Point like a two weeks ago all right so let me ask you a question you know you wrote book

about how to build a mind you have a lot about how the human mind is constructed a lot of the progress in ai ai systems are being built and what we understand about neural networks right so clearly our understanding of this helps with AI in the last two years by watching these large language models have we learned anything new about our brains are we learning about the insides of our skulls as we do this it really has to do with the amount of connections uh the brain is actually organized fairly differently the things near the

eye for example deal with with vision um and we have different ways of implementing different parts of the brain that remember different things we we actually don't need that MH in large language model all the connections are the same we have to get the connections up to a certain point if it approximately matches what the brain does which is about a trillion connections uh it will perform kind of like the brain we're kind of almost at that point wait so dpt4 is 400 billion uh the next ones will be a trillion or more so the

construction of these models they are more efficient in their construction than our brains are we we make them to be as as efficient as possible but it doesn't really matter how they're organized MH and we can actually create certain software that will actually expand the amount of connections more for the same amount of computation um but it really has to do with how how how many connections uh are a particular computer is responsible for so as we approach AGI we're not looking for a new understanding of how to make these machines more efficient the Transformer

architecture was clearly very important we can really just get there more but the software and the learning is also important I mean you could have a trillion connections but if you didn't have something to learn from it wouldn't be very effective so we actually have to be able to collect all this data so we do it on the web and so on I mean we've been collecting stuff on the web uh for several decades uh that's really what we're depending on to be able to to uh train the these large language models and and we

shouldn't actually call them large language models because they deal with much more than language I mean it's language but you can add pictures you can add uh things that affect disease there nothing to do with language uh in fact we're using now simulated biology to to uh to be able to simulate different ways to affect disease um and that has nothing to do with language so they really should be called large event models do you think there's anything that happens inside of our brains that cannot be captured by computation and by math no I mean

what would that be I mean okay quick PLL of the audience raise your hand if you think there's something in your brain that cannot be captured by computation or math like a soul all right so convince them that they're wrong right I mean Consciousness is is very important but it's actually not scientific there's no way I could slide somebody in and the light will go on oh this one's conscious no this one's not uh it's not s it's not scientific but it's actually extremely important uh and another question why am I me how come what

happens to me I'm ious of and I'm I'm not conscious of what happens to you uh these are deeply mysterious things but they're really not it's really not conscious so Marvin Minsky who is my mentor for 50 years he said it's not scientific and therefore we shouldn't bother with it and any discussion of Consciousness he would kind of dismiss but he actually did his reaction to people was totally dependent on whether he felt they were conscious or not so he actually did use that but it's not something that we're ignoring because we there's no way

to to tell whether something's conscious uh and and that's not just something that we don't know and we'll discover there's really no way to to tell whether or not something is conscious what do you mean like this is not conscious and you know the gentleman sitting right there is conscious well how do you prove that I mean um I mean we kind of agree with human that humans are conscious some humans are conscious not all humans um but uh how about animals we have big disagreement some people say animals are not conscious uh and other

people think animals are conscious maybe some animals are conscious and others are not there's no way to prove that let's Okay I want to I want to I want to run down this Consciousness question but before we do that I want to make sure I understood your previous answer correctly so the feeling I get of being in love or the feeling any emotion that I get could eventually be represented in math in a large language model yeah I mean certainly the behavior the feelings that you have if you're with somebody that you love um is

definitely dependent on what the connections do you can tell whether or not that's happening all right um and back to is everybody here convinced not entirely all right well close enough so you don't think that it's worth trying to define consciousness I mean you spend a fair amount in your book giving different arguments about what Consciousness means but it seems like you're arguing on stage that we shouldn't try to Define it there's no way to actually prove it I mean I we have certain agreements I agree that all of you are conscious you actually made

it into this room so that's a pretty good indication that you're conscious uh but that's not a proof uh and and there may be human beings that are don't seem quite conscious at the time are they conscious or not and and animals I mean I think elephants and whales are conscious but not everybody agrees with that so at what point can we then essentially how long will it be until we can essentially download the entire contents of your brain and express it through some kind of a machine that's actually an important question because we're going

to talk about uh longevity uh we're going to get to a point where we have longevity escape velocity and it's not that far away I think if you're diligent you'll be able to achieve that by 2029 that's only five or six years from now um and that so right now you go through a year you use up a year of your longevity but you get back from scientific progress right now about four months but that scientific progress is on an exponential curve it's going to speed up every year and by 2029 if you're diligent you'll

you'll use up a year of your longevity with a year passing but you'll get back a full year and past 2029 you'll get back more than a year uh so you'll actually go backwards in time time now that's not a guarantee of infinite life because um you could have a 10-year-old and you can compute his longevity as many many decades and he could die tomorrow um but what's important about actually capturing everything in your brain we can't do that today and we won't be able to do that in 5 years but you will be able

to do that by the The Singularity which is 2045 and so at that point you can actually go inside the brain and capture everything in there now your thinking is going to be a combination of the amount you get from computation which will add to your thinking and that's that's automatically captured I mean right now anything that's uh you have in uh a computer is automatically captured today and the kind of additional thinking we will have by adding to our brain that will be captured but the the connections that we have in the the brain

uh that we start with we still have that uh that's not captured today but that will be captured in 2045 we'll be able to go inside the brain and capture that as well and therefore we'll actually capture the entire brain uh which will be backed up so even if you get wiped out you walk into a bomb and it explodes we can actually recreate everything that was in your brain uh by 2045 that's one of the implications of the singularity um now that's doesn't absolutely guarantee because uh I mean the world could blow up and

all the uh the computer uh all the things that contain computers could blow up and he still so you wouldn't be able to to recreate that so we never actually get to a point where we absolutely guarantee that you'll live forever but most of the things that uh right now would upset capturing that uh will be overcome by that time let's there's a lot there Ray um let's start with escape velocity so do you think that anybody in this audience in their current biological body will live to be 500 years old you asking me yeah

absolutely and who I mean if you're going to be alive in five years and I imagine all of you will be alive in five years no five okay if they're alive for five years they will likely live to be 500 years old if they're diligent and I think the people in this audience will be diligent so wow all right well you can drink whatever you want as long as you don't get run over tonight because you don't have to worry about decline all right so let me ask a question I want to I want to

get we're going to spend a lot of time on what the singularity is what it means and what it'll be like but I want to ask some questions that'll lead us up there so I'm going to take this question from Mark Sternberg and modify it slightly in the time frame AI will be able to do or sufficiently sophisticated computers in your argument can do everything that the human brain can do what will they not be able to do in the next 10 years well one thing has to do with being creative and some people go

they'll be able to do everything a human can do uh but they're not going to be able to create new knowledge that's actually wrong because we we can simulate for example biology and the the madna vaccine for example we didn't do it the usual way which is somebody sits down and thinks well I think this might work and then they try it out it takes years to try it out and multiple people uh and it's one person's idea about what might work they actually listed everything that might work and there was actually several billion different

mRNA sequences and they said let's try them all and they tried every single one by simulating biology and that took two days so one weekend they tried out several billion different possibilities and then they picked the one that that turned out to be the best and that actually was the the uh madna vaccine U up until today um now they did actually test it on humans we'll be able to overcome that as well because we'll be able to test uh using simulated biology as well they actually decided to test it it's a little bit hard

to give up testing on humans we will do that so you can try out every single one pick the best one and then you can try out that uh by testing on a million simulated humans and do that in a few days as well and that's actually the future of how we're going to create medications for for diseases and there's lots of things going on now with cancer and other diseases uh that are that are using that um so that's that's a whole new method that's actually starting now started right with the majna vaccine we

did another uh uh cure for a mental disease that's actually now in stage three trials uh that's going to be how we create medications uh from now on but what what are the Frontiers what can we not do so so that's where computer is being creative MH and it's not just actually trying something that that occurs to it it makes a list of everything that's possible and tries it all is that creativity or is that just brute force with maximum capability it's much better than uh any other form of creativity and yes it's creative because

you're trying out every single possibility and you're doing it very quickly and you come up with something that we didn't have before I mean what else would creativity be all right so we're going to cross the frontier of creativity what will we not what will we not cross what are the challenges that will be outstanding the next 10 years well we don't everything and we haven't gone through this process it does require some creativity to imagine what might work um and we have to also be able to simulate it in a uh biochemical simulator uh

so we actually have to figure that out and we'll be using people for a while to do that uh so we don't know everything I mean to be able to do everything a human being can do is one thing but there so much we don't know uh that we want to find out and and that requires creativity that will require some kind of human creativity working with machines all right let's go back to what's going to happen to get us to The Singularity so clearly we have the chart that you showed on the power of

comput it's been very steady you know moving straight up you know on a logarithmic scale in a straight line there are a couple of other elements that you you think are necessary to get to the singularity one is the rise of Nanobots and the other is the rise of brain machine interfaces and both of those have gone more slowly than AI so convince the audience that well it would it would be slow because anytime you affect the human body a lot of people are going to be uh concerned about it uh if we do something

with computers we have a new algorithm or um we increased the speed of it um nobody really is concerned about it you can do that no nobody cares about any dangers in it uh I mean that's the reality there's some dangers that people care about yes yeah but it's it goes very very quickly that's one of the reasons it goes so fast uh but if you're affecting the body we have all kinds of concerns that it might affect it negatively and so we want to actually try it on people but but the reason brain machine

interfaces haven't moved in an exponential curve isn't just because you know lots of people are concerned about the risks to humans I mean as you explain in the work in the book they just don't work as well as they could um if we could try things out without having to test it it would go a lot faster I mean that's the reason it goes slowly um but um there's some thought now that we could actually figure out what's going on inside the brain and put things into the brain without actually going inside the brain we

wouldn't need something like brain link uh we could just uh I mean some tests where we can actually tell what's going on in the brain without actually putting something inside the brain and that might actually be a way to do this uh much more quickly but your prediction about the singularity depends maybe I'm reading it wrong not just on the continued exponential birth of compute but on solving this particular problem too right yes because we want to increase the amount of intelligence that humans can can command so we have to be able to marry the

best computers with our actual brain and why do we have to do that because like right now here I go I have my phone in some ways this augments my intelligence it's wonderful but it's very slow I mean if I ask you a question you're going to have to type it in or speak it and it takes a while I mean I ask a question and then people fool around with a computer it might take 15 seconds or 30 seconds it's not like it just goes right into your brain uh I mean these are very

useful these are brain extenders we didn't have these a little while ago uh generally in my talks I ask people who here has their phone I'll bet here maybe there's one or two people but everybody here has their phone uh that wasn't true five years ago definitely wasn't true 10 years ago and it is a brain extender but it does have some speed problems so we want to increase that speed uh a question could could just come up where we're talking and the computer would instantly tell you what the answer is without having to fool

around with an external device uh and that's almost feasible today uh and that and something like that would be helpful to do this but could you not get a lot of the good that you talk about if we just kept the problem with connecting our brains to the machines suddenly you're in this whole world this complicated privacy issues where stuff has being injected in my brain stuff of my brain is you know is going elsewhere like you're opening up a whole host of ethical moral existential problems can't you just make the phones a lot better

well that's the idea that we can do that without uh having to go inside your brain but be able to tell what's going on in your brain externally without going inside the brain uh you know with some kind of device all right well let's keep moving into the future so we're moving into the future we have exponential growth in computer we solve a way of you know ideally figuring out how to communicate directly with your brain to speed things up explain why Nanobots are essential to your vision of where we're going well if you really

want to tell what's going on inside the brain uh you've got to be able to go at at the level of uh the particles in the brain so we can actually tell what they're doing um and that's feasible uh we can't actually do it but we can show that it's feasible um and that's one possibility um we're actually hoping that you could do this without actually affecting the brain at all um okay all right so we're pushing ahead we've got Nanobots that're running around inside of our brain they're understanding our head they're extracting thoughts they're

inputting thoughts let's go to this nice question which hits in lovely from Louise kraa what are the five main ethical questions that we will face as that happens um is four enough four four is fine there might there might even be six Ray but you can give us four I mean we're going to have a lot more power uh if we can actually with our own brain control computers um does that give people too much power uh also I mean right now we talk about having a certain amount of value um based on your um

on your talent this will give talent to people who otherwise don't have talent uh and talent won't be as important uh because you'll be able to gain Talent just by merging with the right kind of large language model or whatever we call them um and it Al also seemed kind of arbitrary why we would give more power to somebody who has more talent because they didn't create that Talent they just happen to have it um and but everybody says we should give uh somebody who has talents in an area more power uh this way you'd

be able to gain Talent uh just in it's in the Matrix you could learn to fly an air a helicopter um just by downloading the right software and supposed to spending a lot of time doing that uh is that fair or unfair um I mean I think that would fall into the ethical challenge area um and it's not like we get to the end of this and say okay this is finally what the singularity is all about and people can do certain things and they can't do other things but it's over we'll never get to

that point I mean this curve is going to continue uh the other curve it's going to continue indefinitely um and we've actually shown for example with nanotechnology we can create a computer where one liter computer would actually match the amount of power that all human beings today have uh like 10 to the 10th persons would all fit into one liter uh computer um does that create ethical problems um so I mean a lot of the implications kind of run against what we've been assuming uh about human beings wait on the talent question which is super

interesting do you feel like everybody when we get to 2040 will have equal capacities I think we'll be more different because we'll have different interests and uh you might be into some fantastic type of music and I might be into some kind of literat or something else I mean we're going to have different interests and so we'll ex excel at certain things depending on what your interests are uh so it's not like we all have the same amount of power but we all have fantastic power compared to what we have today and if you're in

Texas where there are no regulations you'll probably get it first instead of you in massachusett exactly yeah let me ask you another ethical question while we're on this one so about minutes ago you mentioned the capacity to you replicate someone's brain and bring them back so let's say I do that with my father passed away six years ago sadly I bring him back and I'm able to create a mind and a body just like my father's right it's exact perfect replica all his thoughts what happens to the all the bills that he owed when he

died CU like that's a lot of money and a lot of bill collectors call me do we have to pay those off or are we good well we're doing something like that uh with my daughter and you can read about this in her book and it's also in my book uh we collected everything my father had written he died when I was 22 so he's been dead for more than 50 years um and we fed that into a large language model and basically asked her the question uh of all the things he ever wrote uh

what best answers this question and then you can put any question you want uh and then you could talk to it you'd say something You' then go through everything he ever had written and find the best answer that he actually wrote to that question and it actually was a lot of like talking to him could ask him what he liked about music he was a musician uh he actually liked brahs the best um and it was very much like talking to him uh and I reported on this in my book and Amy talks about this

in her book um and Amy actually asked the question could I Fall In Love uh with with this person even though I've never met him and she does a pretty good job I mean you really do fall in love with this character that she creates um even though she never met him um so we can actually with today's technology do something where you can actually emulate somebody else and I think as we get further on we can actually do that more and more uh responsibly and more and more that really would match that person uh

and actually emulate the way he would move and so on his tone of voice well you know my dad he loved Brams too those piano trios so if we can solve the back taxes problem we'll get my dad and your dad's Bots hang out it would be great well yeah that's that'll be cool all right all right we got 20 minutes left I want to get to the thing that I most want to understand because it's something that's by the way this book is wonderful I think you guys are all going to get signed copies

of it when it comes out it's truly remarkable as are all the rais books whether you agree or disagree they will definitely make you think more one of the things that I don't think you do in this book is describe what a day will be like in 2020 2045 when we're all much more intelligent so it's 2045 we're all a million times as intelligent I wake up do I have breakfast or do I not have breakfast well the answer to that question is kind of the same as it is now but um first of all

to the the reason it's called a singularity is because we don't really fully understand that question um Singularity is borrowed from physics singularity in physics is is where you have a black hole and no light can escape and so you can't actually tell what's going on inside the black hole and so we call it a singularity a physical Singularity so this is a historical Singularity but we're borrowing that term from physics they call it a singularity because we can't really answer the question if we actually multiply our intelligence a millionfold what's that like it's a

little bit like asking a mouse gee what would it be like if you had the amount of intelligence of of this person uh the mouse wouldn't really even understand the question uh it does have intelligence has a fair amount of intelligence but it couldn't understand that question it couldn't articulate an answer uh that's a little bit what it would be like for us to take the next step in intelligence by adding all the intelligence that the singularity would provide wa wait I just want to make sure I understand but but but I'll I'll give you

one answer I I said if you're diligent you'll achieve uh longevity escape velocity uh in F in five or six years um and if we want to actually emulate everything that's going on in the in inside the brain uh let's go out a few more years say the 2040 2045 now there's a lot you talk to a person they've got all the connections that they had originally plus all the additional connections that we add um through having them access computers and that becomes part of their thinking um so can you suppose that person like blows

up or something happens to their mind uh you definitely can recreate everything that that's uh of a computer origin because we do that now anytime we create anything with a computer it's backed up so if the computer goes away you've got the back up and you can recreate it says okay but what about their thinking in their normal brain that's not done with computers um we don't have some ways of breing that up when we get to the singularity by 2045 we'll be able to back that up as well uh because we'll be able to

figure out we'll have some ways of actually figuring out what's going on in that uh in that sort of non biolog non mechanical brain um and so we'll be able to back up both their normal brain as well as the compu computer addition um and and and I believe that's feasible by 2045 in your vision of it so so you can back up their entire brain now that doesn't guarantee I mean the whole world could blow up and you lose all the data centers and so it's not absolute guarantee that would be a shame um

but what I don't understand is will we even be fully distinct people if we're sharing memories and we're all uploading our brains to the cloud and we're getting all this information coming back directly into our neocortex are we still distinct uh yes but we could also uh find new ways of communicating so the computers that extend my brain interact with computers that extend your brain we could create something that's like a hybrid or not and it'll be up to our own decision as to whether or not to do that so there'll be some new ways

of communicating let me ask another question about this this is what when I was reading the book this is where I kept getting stuck you are extremely optimistic right you're optimistic about where we are today today you're optimistic that technology has been a massive Force for good you're optimistic that it will continue to be a massive Force for good yet there is a lot of uncertainty in the future you were describing well first of all I'm not uh necessarily optimistic the things that can go wrong uh we had things that that can go wrong before

we had computers um when when I was a child Atomic weapons were uh were created and people were very worried about an atomic war we would actually get under our desk and put our hands behind our head to protect us against an atomic war and seemed to work actually we're still here but if you would ask people um we we had actually two weapons that went off in anger and killed a lot of people within a week and if you ask people what's the chance that we're going to go another 80 years and this will

never happen again nobody would say that that was true but it has happened now that doesn't mean it's not going to happen next week um but anyway that that's a great danger and I think that's a much greater danger than computers are uh yes there are dangers but the computers will also be more intelligent to avoid kinds of dangers um yes it's some bad people in the world but I mean go back 80 90 years um we had 100 million people die in Asia and Europe from World War II uh we don't have wars like

that anymore we could we certainly have the atomic weapons to do that um and you could also Imagine computers could be involved with that um but if you actually look and this goes right through waren pce uh first of all you if you look at my lineage of computers going from Tiny fraction of one calculation to 65 billion that's a 20 quadrillion fold increase that we've uh achieved in 80 years and look at this us personal income this is done in constant dollars so this has nothing to do with inflation uh and this is the

the average income in the United States um it went it's multiplied by about 100f fold um and we live far more SU successfully if you actually people say oh things were great 100 years ago they weren't um and you can look at this chart most of I've got 50 charts in the book that show the kind of progress we've made uh number of people that that live and dire or poverty has gone down dramatically and we actually did a poll where they asked people uh people that live in poverty has they gone up or down

80% said it's it's gone up but the the reality is it's actually Fallen by 50% uh um in the last 20 years so so what we think about the past is is is really the opposite of what's happened things have gotten far better than they have and computers are going to make things even better I mean just the kind of things you can do now with a large language model didn't exist too years ago do you ever worry that take it as a given the compers have made things better take it as a given that

personal income will keep going up do you ever worry it's just coming too quickly and it'll be better if maybe the slope of the Curts wild curve was a little less that's a big difference in the past I mean talk about what effect did the railroad have uh I mean lots of jobs were lost or even the cotton Jenny that happened 200 years ago uh and people were quite happy making money with the cotton Jenny and suddenly that was gone and machines were doing that and people say well wait till this gets going all jobs

will be lost and that's actually what uh was said at that time um but actually income went up more and more per people worked we created and if you say well what are they going to do you couldn't answer that question because it was in industry that nobody uh had a clue of like for example all of electronics um so things are getting better even if jobs are lost now you can certainly point to jobs like like take computer programming um Google has I don't know 60,000 people that that program computers and lots of other

companies do uh at some point that's not going to be a feasible uh job they can already code lots of language models can write code not quite the way an expert programmer can do but how long is that going to take it's measured in years not in decades um nonetheless I believe that things will get better because we wipe out uh jobs but we create other way ways of of having an income uh and if you actually point to something let's say this machine and this is being worked on can wash dishes you just have

a bunch of dishes it'll pick the the ones that have to go in the dishwasher and clean everything else up and that will wash dishes for you would we want that not to happen uh would we say well this is kind of upsetting things let's get rid of it it's not going to happen and no one would would Advocate that um so we'll find things to do we'll have other methods of Distributing money um and it will be it'll continue these kinds of curves that we've seen already it's kind of remarkable that we got large

language models before we got robotic dishwashers um you have grandchildren you know what do you what would you tell a young person you know they buy in they agree that or you know how would you tell them to best prepare themselves for what will be a if you're correct a remarkably different future uh I'd be less concerned about what will make money and much more concerned about what turns them on um they they love video games so they should learn about that uh they should read literature that turns them on some of those literature in

the future will be created by computers but um and find out what in the world uh has a positive effect on their mental being and if you know that your child or your grandchild this gets to one of the questions that is asked on the on the screen here if you know that someone is going to live for hundreds of years years as you predict how does that affect the way certainly means they shouldn't retire at 65 but what else does it change about the way they should think about their lives well I talk to

people and they say well I I wouldn't want to live past 100 or would or maybe they're a little more ambitious to say I don't want to live past 110 um but if you actually look and when people decide they've had enough and they don't want to live anymore that never ever happens unless these people are in some kind of dire pain they're in physical pain or emotional pain or spiritual pain or whatever and they just cannot bear to be alive anymore nobody takes their lives other other than that and if we can actually overcome

many kinds of physical problems uh cancer wiped out and so on which I expect to happen uh people will be even that much more happy to live and they'll they'll want to continue uh to experience tomorrow and tomorrow is going to be better and better uh these kinds of progress It's not going to go away um so people will want to live um you know unless they're in dire pain but that's what the whole sort of medical profession is about which is going to be greatly Amplified by tomorrow's computers let me ask you a great

question that has popped on the screen this is from Colin mccab AI is a black box nobody knows how it was built how do you show that AI is trustworthy to users who want to trust it adopt it and accept it particularly if you're going to upload it directly into your brain well it's not true that nobody knows how they work right um most people who are using a large language model don't know what data sense went into it there are things that happen at the Transformer layer that even The Architects don't understand right but

we're going to learn more and more about that uh and in fact how computers work will be I think very common uh type of talent that people want to gain um and ultimately we'll have more Trust of computers I mean large language models aren't perfect then you can ask it a question I can give you something that's incorrect um I mean we've seen that just recently uh the reason we have the these computers give you incorrect information is it doesn't have the information to begin with and it actually doesn't know what it doesn't know and

that's actually something we're working on uh so that it knows well I don't know that uh that's actually very good if it can actually say that because right now it'll find the best thing it knows and if it if it's never trained on that information and there's nothing in there that tells you it'll just give you the best guess which could be very incorrect uh and we're actually learning to be able to figure out when it knows and when it doesn't know uh but ultimately we'll have pretty good um confidence when it knows and what

it doesn't know and we can actually rely on what it says so your answer to the question is a we will understand more and B they'll be much more trustworthy so it won't be as risky to not understand them right okay you've you've spent your life making predictions some of which like the Turing test you've held on to and been remarkably accurate As you move from a overwhelming Optimist to now slightly of a pessimist what is a prediction well my books have always had a chapter on on how these things can go wrong and perils

tell me a prediction that you are chewing over right now but you're not sure whether you want to make it or whether you don't want to make it um I mean there there's well-known dangers in uh nanotechnology uh if someone were to create a nanotechnology that replicates well welln is if it replicates everything into paper clips uh turn the entire world into paper clips uh that would not be positive no and and you unless you're Staples but then and and that's feasible uh take somebody who's uh a little bit mental to do that but it

it it could be done um and we actually will have something that actually avoids that um so we'll have something that can detect that this is actually turning everything into paper clips and destroy it before it it does that um but I mean I have a chapter in this new book The singulari is nearer um that talks about the kinds of things that could happen oh the most remarkable part of this book is he does exactly the mathematical calculations on how long it would take Nanobots to turn the world into gray goo and how long

it would take the blue goo to stop the greay goo is remarkable the book will be out soon you definitely need to read until the end but this leads to it maybe let me try and answer the question I asked before is what should young people think about and be working on you said they're passions and what turns them on shouldn't they be thinking through how to design and architect these future systems so they are less likely to turn us into GR paper I don't know if everybody wants to work on that but but folks

in this room right technologically minded you guys should all be working on not turning us into greay goo right yes that'll be on the list you but but then that leads to another question which is what will the role of humans be in thinking through that problem when they're only a million or a billion or a trillion as intelligent as machines say that again so we're going to have these really hard problems to solve yeah right right now we are along with our machines you know we can be extremely intelligent but 10 years from now

15 years from now there will be machines that will be so much more intelligent than us what will our role what will the role of humans be in trying to solve I see those as extensions of humans and we wouldn't have them if we didn't have humans to begin with and humans have a brain that can think these things through and we have this thumb it's not really very much appreciated but like whales and elephants actually have a larger brain than we have and they can probably think deeper thoughts but they don't have a thumb

and so they don't create technology uh monkey can create it actually has a thumb but it's actually down an inch or so and therefore it really can't grab very well so it can create a little bit of technology but the technology it creates cannot create other technology so the fact that we have a thumb means we can create uh integrated circuits that can become a large language model uh that that that comes from the human brain um and it rep and it's actually trained with everything that we've ever thought anything that that human beings have

thought it's been documented and and it can go into these large Lang models um and everybody can work on these things and it's not true well only certain wealthy people will have it I mean how many people here have phones it's that's if it's not 100% it's like 99.9% and and you don't have to be kind of from a wealthy group I mean I see people who are homeless who have their own phone uh it's it's not that expensive um and so that represents the distribution of of these capabilities it's not something you have to

be fabulously wealthy to afford so you think that we're heading into a future where we're going to live much longer and we be much more equal say again we you think we're heading into a society where we'll live much longer be wealthier but also much more equality yes absolutely and we've seen that already all right well we are at time but Ray and I will be back in 2124 2224 and 2324 so thank you for coming today thank you so much he is an American treasure thank you r [Music]